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Transcriptomic profiling of pancreatic stellate cells and pancreatic cancer cells in a gemcitabine-driven tumor-stroma supernatant transfer model

GSE324779 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/03/18 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
12 samples: 3 × PSC4 cells treated with Control-SU, vs 3 × PSC4 cells treated with Gem-SU, vs 3 × KPC4 cells treated with Control-PSC-SU, vs 3 × KPC4 cells treated with Gem-PSC-SU,Groups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive tumor-stroma interactions that influence disease progression and therapy response. To investigate transcriptional changes associated with chemotherapy-induced tumor-stroma signaling, RNA sequencing was performed in a supernatant transfer system. Murine pancreatic cancer cells (KPC4) were treated with gemcitabine, and supernatants from gemcitabine-treated or vehicle-treated tumor cells were transferred to murine pancreatic stellate cells (PSC4).
Read the full summary ↓
In a second experiment, supernatants from PSC4 cells previously exposed to tumor cell supernatants were transferred back to pancreatic cancer cells. RNA sequencing was performed to characterize gene expression changes associated with chemotherapy-induced tumor-stroma communication.
This dataset
Open GSE324779 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE324779_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1435881 and SRA study SRP682957. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × PSC4 cells treated with Control-SU, vs 3 × PSC4 cells treated with Gem-SU, vs 3 × KPC4 cells treated with Control-PSC-SU, vs 3 × KPC4 cells treated with Gem-PSC-SU,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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